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White Matter Connectivity Predicts Autism Spectrum Disorder Symptom Severity in High-Functioning Young Adults

Thursday, 2 May 2013: 14:00-18:00
Banquet Hall (Kursaal Centre)
C. R. Gibbard1, J. Ren2, K. K. Seunarine1, J. D. Clayden1, D. H. Skuse2 and C. A. Clark1, (1)Imaging and Biophysics Unit, UCL Institute of Child Health, London, United Kingdom, (2)Behavioural and Brain Sciences Unit, UCL Institute of Child Health, London, United Kingdom
Background: Increasing evidence suggests that autism spectrum disorder (ASD) occurs at the extreme of a distribution of social and communication abilities.  Diffusion tensor imaging (DTI) studies have shown white matter (WM) abnormalities in tracts involved in social processing in ASD.  However, little is known about the relationship between these WM anomalies and the range of behavioural phenotypes observed in ASD and the neurotypical population.  Further, the majority of DTI studies in ASD have focussed on children and adolescents.  Little is therefore known if the reported WM abnormalities persist into adulthood.

Objectives: We investigated WM microstructure and its relationship to ASD symptom severity across both ASD adults and neurotypical controls using tract-based spatial statistics (TBSS), a whole-brain voxel-based approach.  TBSS mitigates registration and smoothing effects found in alternative techniques and enables investigation of the whole WM without prior hypotheses of regions of interest.

Methods: 25 high-functioning ASD (mean age 24.5yr) and 25 neurotypical subjects (mean age 23.22yr) underwent whole-brain T1-weighted (1mm isotropic) and diffusion-weighted (2.5mm isotropic; 60 directions at b=1000s/mm2; 3 interleaved b=0s/mm2) MRI on a 1.5T Siemens Avanto scanner.  The diffusion data were pre-processed using FSL, including eddy current correction and brain-extraction.  Subsequently, voxel-wise WM analysis was performed using TBSS that co-registers all diffusion data and generates an average WM skeleton on which statistical comparisons are made.  The values for each DTI metric were also averaged across the WM skeleton and correlated with the autism quotient (AQ), a self-reported measure of autistic symptoms.  Age, gender, full-scale IQ and whole brain volume were added as nuisance covariates in all analyses.

Results: Voxel-wise analysis of the WM skeleton using TBSS showed widespread regions of significantly reduced fractional anisotropy (FA) and significantly increased mean diffusivity (MD) and radial diffusivity (RD) in ASD compared to controls.  Across the whole study population, FA averaged across the WM skeleton was negatively correlated with AQ score (rho=-0.38; p=0.007) in ASD, whilst AQ was positively correlated with MD (rho=0.46; p=0.0009) and RD (rho=0.46; p=0.0008).  These correlations were predominately localized in the left hemisphere. Correlations between DTI parameters and subdivisions of the AQ score were strongest for social, communication and attention switching domains and weakest for attention to detail and imagination.

Conclusions: Our finding of very widespread reductions in FA and increases in MD and RD in ASD compared to neurotypical controls suggests that WM microstructural changes in ASD adults are more widely distributed than previously reported.  The correlations between WM anomalies and the severity of ASD traits across the whole study population indicate that WM microstructural aberrations form a distribution which is strongly related to a spectrum of abnormal social behaviours, of which ASD is at the extreme.  The specific relationships between DTI parameters and sub-divisions of the AQ score suggest that the distributed structural-functional relationship is strongest for social communication ASD traits.  Our finding of a separation of IQ from the relationship between WM microstructure and ASD severity is evidence for distinction of core cognitive abilities from the social difficulties central to ASD.

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